Commitment in Interracial Relationships: Dyadic and Longitudinal Tests of the Investment Model

2018 ◽  
Vol 39 (9) ◽  
pp. 2685-2708 ◽  
Author(s):  
James E. Brooks ◽  
Brian G. Ogolsky ◽  
J. Kale Monk
Keyword(s):  
Empirical Research ◽  
Interracial Relationships ◽  
Investment Model ◽  
Relationship Commitment ◽  
Model Fit ◽  
Intraracial Relationships ◽  
Better Than

Empirical research to explain why partners in interracial relationships appear to be less committed than partners in intraracial relationships is scarce. The Investment Model has been shown to be a robust predictor of relationship commitment, but has only been applied to interracial relationships on a few occasions. Using a sample of 232 couples ( n = 172 intraracial; n = 60 interracial), we found the Investment Model performs comparatively well in interracial and intraracial relationships. However, there were some differences in the influence of investments on commitment. Investments were associated with concurrent commitment in intraracial but not interracial relationships, and an interdependent version of the Investment Model (Actor–Partner Interdependence Investment Model) fit intraracial relationships better than interracial relationships. The results suggest there are nuances in applying the Investment Model to interracial relationships, but that the model is promising for understanding the commitment of partners who experience marginalization.

Exploring the Multidimensional Facets of Authoritarianism: Authoritarian Aggression and Social Dominance Orientation

2008 ◽  
Vol 67 (1) ◽  
pp. 51-60 ◽  
Author(s):  
Stefano Passini
Keyword(s):  
Social Dominance ◽  
Factor Model ◽  
Three Dimensional ◽  
Social Dominance Orientation ◽  
Model Fit ◽  
Regression Analyses ◽  
One Dimensional ◽  
Confirmatory Factor ◽  
The One ◽  
Better Than

The relation between authoritarianism and social dominance orientation was analyzed, with authoritarianism measured using a three-dimensional scale. The implicit multidimensional structure (authoritarian submission, conventionalism, authoritarian aggression) of Altemeyer’s (1981, 1988) conceptualization of authoritarianism is inconsistent with its one-dimensional methodological operationalization. The dimensionality of authoritarianism was investigated using confirmatory factor analysis in a sample of 713 university students. As hypothesized, the three-factor model fit the data significantly better than the one-factor model. Regression analyses revealed that only authoritarian aggression was related to social dominance orientation. That is, only intolerance of deviance was related to high social dominance, whereas submissiveness was not.

Modeling of Nonlinear Viscoelastic Creep of Polycarbonate

e-Polymers ◽  
2007 ◽  
Vol 7 (1) ◽  
Author(s):  
Wenbo Luo ◽  
Said Jazouli ◽  
Toan Vu-Khanh
Keyword(s):  
Creep Behavior ◽  
Room Temperature ◽  
Multiple Integral ◽  
Model Fit ◽  
Viscoelastic Creep ◽  
Commercial Grade ◽  
Nonlinear Viscoelastic ◽  
Schapery Model ◽  
Special Case ◽  
Better Than

AbstractThe creep behavior of a commercial grade polycarbonate was investigated in this study. 10 different constant stresses ranging from 8 MPa to 50 MPa were applied to the specimen, and the resultant creep strains were measured at room temperature. It was found that the creep could be modeled linearly below 15 MPa, and nonlinearly above 15 MPa. Different nonlinear viscoelastic models have been briefly reviewed and used to fit the test data. It is shown that the Findley model is a special case of the Schapery model, and both the Findley model and the simplified multiple integral representation are suitable for properly describing the creep behavior of the polycarbonate investigated in this paper; however, the Findley model fit the data better than the simplified multiple integral with three terms.

scholarly journals The updated Charlson comorbidity index is a useful predictor of mortality in patients with Staphylococcus aureus bacteraemia

2018 ◽  
Vol 146 (16) ◽  
pp. 2122-2130 ◽  
Author(s):  
H. G. Ternavasio-de la Vega ◽  
F. Castaño-Romero ◽  
S. Ragozzino ◽  
R. Sánchez González ◽  
M. P. Vaquero-Herrero ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Charlson Comorbidity Index ◽  
Regression Models ◽  
Model Fit ◽  
Logistic Regression Models ◽  
Relevant Variables ◽  
Comorbidity Index ◽  
The Mean ◽  
Related Mortality ◽  
Better Than

AbstractThe objective was to compare the performance of the updated Charlson comorbidity index (uCCI) and classical CCI (cCCI) in predicting 30-day mortality in patients with Staphylococcus aureus bacteraemia (SAB). All cases of SAB in patients aged ⩾14 years identified at the Microbiology Unit were included prospectively and followed. Comorbidity was evaluated using the cCCI and uCCI. Relevant variables associated with SAB-related mortality, along with cCCI or uCCI scores, were entered into multivariate logistic regression models. Global model fit, model calibration and predictive validity of each model were evaluated and compared. In total, 257 episodes of SAB in 239 patients were included (mean age 74 years; 65% were male). The mean cCCI and uCCI scores were 3.6 (standard deviation, 2.4) and 2.9 (2.3), respectively; 161 (63%) cases had cCCI score ⩾3 and 89 (35%) cases had uCCI score ⩾4. Sixty-five (25%) patients died within 30 days. The cCCI score was not related to mortality in any model, but uCCI score ⩾4 was an independent factor of 30-day mortality (odds ratio, 1.98; 95% confidence interval, 1.05–3.74). The uCCI is a more up-to-date, refined and parsimonious prognostic mortality score than the cCCI; it may thus serve better than the latter in the identification of patients with SAB with worse prognoses.

Linear mixed model better than repeated measures analysis

2019 ◽  
Vol 30 (6) ◽  
pp. NP1-NP2 ◽  
Author(s):  
Işıl Kutluturk Karagoz ◽  
Berhan Keskin ◽  
Flora Özkalaycı ◽  
Ali Karagöz
Keyword(s):  
Mixed Models ◽  
Repeated Measures ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Linear Time ◽  
Case Series ◽  
Model Fit ◽  
Repeated Measures Analysis ◽  
Technical Issues ◽  
Better Than

We have some criticism regarding some technical issues. Mixed models have begun to play a pivotal role in statistical analyses and offer many advantages over more conventional analyses regarding repeated variance analyses. First, they allow to avoid conducting multiple t-tests; second, they can accommodate for within-patient correlation; third, they allow to incorporate not only a random coefficient, but also a random slope, typically ‘linear’ time in longitudinal case series when there are enough data and patients’ trajectories vary a lot and improving model fit.

Pixel-level Signal Modelling with Spatial Correlation for Two-Colour Microarrays

2005 ◽  
Vol 4 (1) ◽  
Author(s):  
Claus T Ekstrøm ◽  
Søren Bak ◽  
Mats Rudemo
Keyword(s):  
Spatial Correlation ◽  
Substantial Improvement ◽  
Model Fit ◽  
Oligonucleotide Microarrays ◽  
Data Set ◽  
Pixel Intensity ◽  
Spherical Models ◽  
Correlation Structures ◽  
Signal Modelling ◽  
Better Than

Statistical models for spot shapes and signal intensities are used in image analysis of laser scans of microarrays. Most models have essentially been based on the assumption of independent pixel intensity values, but models that allow for spatial correlation among neighbouring pixels can accommodate errors in the microarray slide and should improve the model fit. Five spatial correlation structures, exponential, Gaussian, linear, rational quadratic and spherical, are compared for a dataset with 50-mer two-colour oligonucleotide microarrays and 452 probes for selected Arabidopsis genes. Substantial improvement in model fit is obtained for all five correlation structures compared to the model with independent pixel values, and the Gaussian and the spherical models seem to be slightly better than the other three models. We also conclude that for the data set analysed the correlation seems negligible for non-neighbouring pixels.

scholarly journals On the Role of Distinctive Features of British English Sounds in the Cartoon Peppa Pig for Chinese Learners to Conquer Mother Tongue’s Negative Transfer

2021 ◽  
Vol 4 (4) ◽  
pp. 65
Author(s):  
Gang Li
Keyword(s):  
Second Language ◽  
Empirical Research ◽  
Negative Transfer ◽  
British English ◽  
Distinctive Features ◽  
Starting Point ◽  
Chinese Learners ◽  
Better Than

With the process of globalization and integration, more and more people tend to be bilingual. Undoubtedly, mastering a second language is significant. This thesis aims to explore how to conquer the difficulties in learning British English sounds through analyzing a British cartoon Peppa Pig.Chapter one begins with the research background, significance and purpose of research. The thesis takes the cartoon Peppa Pig as the starting point to demonstrate the role of distinctive features for Chinese learners to conquer negative transfer. The empirical research could be found in Chapter two, because of requiring to know the concrete circumstance of Chinese learners.Through the collection and analysis of data, we can know these problems which Chinese learners exist in the process of learning British English.Based on the comparison of Chinese and British English, Chapter three clarifies the difficulties in learning British English. As for Chinese learners, mastering distinctive features can promote learners to master British English sounds better than stress and rhythm. Chapter four states the role of the distinctive features in helping conquer Chinese negative transfer in the cartoon Peppa Pig. The final chapter is the conclusion of this thesis and involves a new study for Chinese learners to learn British English sounds under the distinctive features.

Evaluation of Structural Equation Modeling Estimates of Reliability for Scales with Ordered Categorical Items

Methodology ◽  
2015 ◽  
Vol 11 (1) ◽  
pp. 23-34 ◽  
Author(s):  
Yanyun Yang ◽  
Samuel B. Green
Keyword(s):  
Structural Equation ◽  
Monte Carlo Study ◽  
Reliability Coefficient ◽  
Model Fit ◽  
Equation Modeling ◽  
Single Administration ◽  
Ordered Categories ◽  
Normality Assumption ◽  
Ordered Categorical ◽  
Better Than

Different methods are reviewed for estimating reliability based on a single administration of a test consisting of ordered categorical items. The nonlinear SEM reliability coefficient appears more flexible than other methods because it is designed to assess the reliability of summed scores for ordered categorical items through the modeling of the item relationships. However, this method assumes that the variables underlying the ordered categorical items are normally distributed. We evaluated nonlinear and linear SEM reliability coefficients using a Monte Carlo study by manipulating factor structure, distribution of the continuous items, number of ordered categories, distribution of the ordered categorical items, and sample size. The nonlinear SEM reliability coefficient performed as well as or better than the linear SEM reliability coefficient in most conditions and was relatively robust to modest violations of the normality assumption. The nonlinear SEM reliability coefficient was substantially biased when categorical item distributions were extremely skewed and the skewness differed markedly across items. Bias in these coefficients may be diagnosable in practice by assessing model fit.

Replication of a tri-level model of anxiety and depression in a sample of young adults

2019 ◽  
Author(s):  
Amanda Marie Kramer ◽  
Nicholas J. Kelley ◽  
Iris Ka-Yi Chat ◽  
Katherine Seaton Young ◽  
Robin Nusslock ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Young Adults ◽  
Anxiety Disorders ◽  
Model Fit ◽  
Anxiety And Depression ◽  
Specific Factor ◽  
General Distress ◽  
Level Model ◽  
The Relationship ◽  
Better Than

The wide array of symptoms of unipolar depressive and anxiety disorders has raised questions about the relationship between these disorders, and factor analysis provides one approach to examining these relationships. In this paper, we replicate the tri-level model of symptoms of anxiety and depression first proposed by Prenoveau et al. (2010) in a sample of young adults selected to vary in their risk for psychopathology. In the tri-level model, symptom-specific items load on three factors arranged in a bifactor structure: a narrow (or disorder-specific) factor, an intermediate (or category-specific) factor, and a general distress factor. The tri-level model fit well in this sample. Furthermore, it fit significantly better than models that eliminated one of the three levels, suggesting that each level of the tri-level model contributes significantly to model fit. This conceptual replication once again supports the tri-level model. Implications for research and treatment are discussed.

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